The following abbreviations are used in this specification:
eICICenhanced inter-cell interference coordinationFDDfrequency division duplexingFDMAfrequency division multiple accessIIRinfinite impulse responseIRCinterference rejection combiningLTELong Term EvolutionLTE-ALong Term Evolution - AdvancedNOCEnoise covariance matrix estimateOFDMorthogonal frequency division multiplexingOFDMAorthogonal frequency division multiple accessPRBphysical resource blockRATradio access technologySC-FDMAsingle-carrier frequency division multiple accessTDDtime division duplexingTDMAtime division multiple accessUEuser equipment
In cellular systems, such as the one illustrated schematically in FIG. 1, the quality of a signal received by a receiver 100 from a transmitter 110 can be detrimentally affected by various types of noise, such as interfering signals from other nearby transmitters 120 (for example a base station in a neighboring cell), thermal noise within the receiver 100 itself, and other sources 130. In some cases, noise can affect the quality of a received signal so much that effective reception of data is severely impaired. Thus, to ensure that data is correctly and consistently extracted from a received signal, methods must be implemented that keep the amount of noise interfering with the signal to a minimum and/or that enable the identification and rejection of any noise within a received signal. The latter method is of particular importance for RATs (radio access technologies) that use the same or similar frequency spectrum in adjacent cells, as interference of signals from adjacent cells is inherently high and such systems must rely on interference rejection techniques to remove noise in signals. A particular example is RATs that use LTE (Long Term Evolution) or LTE-A (Long Term Evolution—Advanced) specifications.
There are several techniques known in the prior art for removing noise from a received signal. One such technique is known as Interference Rejection Combining (IRC), which can be used if a receiver 100 has at least two spatially separate antennas 140 or at least two differently polarized antennas 140. A receiver 100 using IRC will receive signals carried on a particular channel via its two (or more) antennas, and will then process these signals separately. The receiver 100 may then combine these processed signals by assigning weightings to each of the processed signals (received by the different antennas) and then adding the weighted signals together. The weightings are assigned according to a noise covariance matrix estimate (NOCE), which represents an estimation of the correlation between the noise received at each antenna. A NOCE is a NRX×NRX matrix, where NRX is the number of antennas the receiver 100 has. It will be understood that in general “channel” can refer to one or more carrier signals broadcast within a certain time frame or frequency band or with a particular coding, or any combination thereof.
There are a number of known techniques used to calculate NOCEs, many of which use noise vectors nv,t in NOCE calculations. Noise vectors have dimensions of NRX×1, and each element of the noise vector is an estimate of the amount of noise received by a particular antenna for a signal received by a receiver 100 at a particular time and with a particular frequency (v and t denoting frequency and time respectively).
Noise received in a particular channel is in general both frequency and time dependent due to frequency and time selective fading and also because nearby interfering wireless devices or UEs may have different transmission ranks and pre-codings. This means that, in general, there can be a number of different noise vectors representing differing amounts of noise received at different times and/or frequencies all within the same channel.
A well known method for estimating a NOCE involves first forming intermediate matrices from noise vectors according to Eqn. 1:Cv,t=nv,tnv,tH  Eqn. 1where nv,tH is the conjugate transpose of the noise vector nv,t representing the noise received at different antennas of a receiver 100 for a signal with frequency v transmitted at time t, and Cv,t is the intermediate matrix for a signal with frequency v transmitted at time t.
A NOCE for noise received in a particular channel can then be calculated by averaging all the intermediate matrices for times and frequencies within that channel. A number of techniques for averaging these different intermediate matrices are known. For example, in one case, a NOCE may be calculated according to a weighted average as shown below in Eqn. 2:C(q)=Σv,twv,tnv,tnv,tH=Σv,twv,tCv,t  Eqn. 2
Here, C(q) is an NOCE for noise received in a particular channel “q” and wv,t is a weighting coefficient, which is frequency and time dependent. The summation may include times and frequencies both within and outside the particular channel q. In the most simple case, all of the intermediate matrices Cv,t may be equally weighted. In another example, weightings may be higher for intermediate matrices Cv,t for frequencies and/or times within the channel q, and lower for intermediate matrices for frequencies and/or times outside the channel q. In all cases, the weightings are predetermined fixed values.
As another example, a NOCE for noise received in a particular channel can be calculated by first filtering the intermediate matrices Cv,t using a fixed filter, which may for example remove intermediate matrices Cv,t for frequencies and/or times that are far away from the frequencies and/or times within the channel q. An example of such a filter is an Infinite Impulse Response (IIR) filter. After being filtered, the remaining intermediate matrices Cv,t may be averaged as described above.
In these prior art techniques, the weightings and/or filters applied to the intermediate matrices Cv,t are applied either in a fixed manner, or according to some global parameter, which may be, for example, an estimate of the channel delay spread or, as another example, an estimate of the maximum Doppler frequency. Thus these weightings and/or filters do not have the capacity to accommodate any sudden or unexpected local changes in interference properties in the frequency and/or time domains. For example, if a NOCE estimate is obtained by averaging over intermediate matrices Cv,t (as described above) for frequencies and times that see significantly different amounts of noise in terms of power and spatial signature, then the NOCE estimate may be inaccurate and, consequently, the performance of IRC may be compromised.